code: def update_submit_s3_uri(estimator, job_name):
      """Updated the S3 URI of the framework source directory in given estimator.
  
      Args:
          estimator (sagemaker.estimator.Framework): The Framework estimator to
              update.
          job_name (str): The new job name included in the submit S3 URI
  
      Returns:
          str: The updated S3 URI of framework source directory
      """
      if estimator.uploaded_code is None:
          return
  
      pattern = r"(?<=/)[^/]+?(?=/source/sourcedir.tar.gz)"
  
      # update the S3 URI with the latest training job.
      # s3://path/old_job/source/sourcedir.tar.gz will become s3://path/new_job/source/sourcedir.tar.gz
      submit_uri = estimator.uploaded_code.s3_prefix
      submit_uri = re.sub(pattern, job_name, submit_uri)
      script_name = estimator.uploaded_code.script_name
      estimator.uploaded_code = fw_utils.UploadedCode(
          submit_uri, script_name
      )
  
imports: from __future__ import print_function, absolute_import
  import os
  import re
  import sagemaker
  from sagemaker import fw_utils, job, utils, s3, session, vpc_utils
  from sagemaker.amazon import amazon_estimator
  from sagemaker.tensorflow import TensorFlow
  from sagemaker.estimator import EstimatorBase
  from sagemaker.processing import Processor
  from sagemaker.utils import format_tags
label_desc: Use image node_id 10 for calling a global function with example usage: update_submit_s3_uri(estimator, job_name) without return types